── Attaching core tidyverse packages ──────────────────────────────────────────────────────────────────────── tidyverse 2.0.0 ──
✔ dplyr 1.1.4 ✔ readr 2.1.5
✔ forcats 1.0.0 ✔ stringr 1.5.1
✔ ggplot2 3.4.4 ✔ tibble 3.2.1
✔ lubridate 1.9.3 ✔ tidyr 1.3.0
✔ purrr 1.0.2 ── Conflicts ────────────────────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()
ℹ Use the ]8;;http://conflicted.r-lib.org/conflicted package]8;; to force all conflicts to become errors
library(ggplot2)
library(tsibble)
Attaching package: ‘tsibble’
The following object is masked from ‘package:lubridate’:
interval
The following objects are masked from ‘package:base’:
intersect, setdiff, union
library(fabletools)
library(readxl)
library(openxlsx)
Descripción de AMZN
Amazon es una de las empresas tecnológicas y de comercio electrónico
más grandes del mundo, fundada en 1994 por Jeff Bezos en Seattle,
Washington. Inicialmente comenzó como una tienda en línea de libros,
pero ha crecido exponencialmente para ofrecer una amplia gama de
productos y servicios, incluyendo electrónicos, ropa, alimentos,
servicios en la nube, entretenimiento digital, inteligencia artificial y
dispositivos de consumo. La empresa se ha expandido globalmente, con
presencia en múltiples países y regiones. Amazon es conocida por su
enfoque en la innovación, la eficiencia operativa y la atención al
cliente. Su plataforma de comercio electrónico, Amazon.com, es una de
las más visitadas del mundo. Además, Amazon Web Services (AWS) es uno de
los proveedores líderes de servicios en la nube, brindando
infraestructura informática a empresas y organizaciones de todos los
tamaños. Amazon también ha incursionado en la producción de contenido
original a través de su división de entretenimiento, Amazon Studios, y
ha desarrollado una serie de dispositivos de hardware populares, como
los altavoces inteligentes Echo y los lectores de libros electrónicos
Kindle. La empresa está constantemente buscando expandirse en nuevos
mercados y áreas de negocio, y su impacto en la economía y la sociedad
global es significativo.
Datos
Importar
amzn_csv <- read.csv("AMZN.csv")
Cambiar tipo de datos
amzn_csv$Date = ymd(amzn_csv$Date)
Crear tsibble
amzn <- amzn_csv %>%
as_tsibble(index = Date)
amzn
[1] "tbl_ts" "tbl_df" "tbl" "data.frame"
Análisis
Visualización de la serie
Time plot
amzn |>
autoplot(Close) +
labs(y = "Prices", title = "Historic Prices AMZN")

Patrones y Estacionalidad
feasts::autoplot(amzn) + ggtitle('Historical graphic AMZN') + ylab('Prices') + xlab('Date')
Plot variable not specified, automatically selected `.vars = Open`

library(tsibble)
library(feasts)
library(plotly)
Registered S3 method overwritten by 'data.table':
method from
print.data.table
Registered S3 method overwritten by 'htmlwidgets':
method from
print.htmlwidget tools:rstudio
Attaching package: ‘plotly’
The following object is masked from ‘package:ggplot2’:
last_plot
The following object is masked from ‘package:stats’:
filter
The following object is masked from ‘package:graphics’:
layout
amzn$Adj.Close = as.numeric(amzn$Adj.Close)
head(amzn, 2)
amzn_filled <- fill_gaps(amzn)
amzn_filled %>%
gg_season(Adj.Close, labels = "both") +
ggtitle('Historical graphic AMZN') +
ylab('Price') + xlab('Date')

yearly_amzn_plot = amzn_filled %>% gg_season(Adj.Close, labels = "both") +
ggtitle('Yearly historical graphic AMZN ') + ylab('Date') + xlab('Price')
ggplotly(yearly_amzn_plot)
Gráfico de Rezagos
lags_plots = amzn_filled %>%
filter(year(Date) > 2022) %>%
gg_lag(Adj.Close, geom = "point", lags = 1:12) +
labs(x ="lag(Precio, k)")
Warning: Removed 113 rows containing missing values (gg_lag).
suppressWarnings(ggplotly(lags_plots))
amzn_filled %>% ACF(Adj.Close, lag_max = 12)
Autocorrelación
amzn_filled %>% ACF(Adj.Close, lag_max = 24) %>% autoplot() + labs(title='Historical price AMZN')

Estadística descriptiva
summary(amzn$Adj.Close, 'value')
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.2985 2.2695 10.2720 37.9091 59.6800 186.5705
Medidas de dispersión
Attaching package: ‘EnvStats’
The following objects are masked from ‘package:stats’:
predict, predict.lm
[1] 0.5085591
[1] 1.364781
[1] 51.5428
[1] 2656.66
library(ggExtra)
p <- ggplot(amzn_filled, aes(x=Date, y=Adj.Close)) +
geom_hline(yintercept =25) +
geom_hline(yintercept =150) +
geom_point() +
ggtitle('Historical graphic AMZN') + ylab('Price') + xlab('Date')
ggMarginal(p, type='histogram', margins = 'y')
Warning: Removed 2725 rows containing missing values (`geom_point()`).Warning: Removed 2725 rows containing missing values (`geom_point()`).


histogram = ggplot(amzn_filled, aes(x = Adj.Close)) +
geom_histogram( bins = 20, fill = "black", color = "black", alpha = 0.5) +
labs(title = "Histograma",
x = "Price",
y = "Densidad")
ggplotly(histogram)
Warning: Removed 2725 rows containing non-finite values (`stat_bin()`).
Valores atípicos

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